class_docstr: Wayburn and Seader 2 objective function.
  
  This class defines the Wayburn and Seader 2 [1]_ global optimization
  problem. This is a unimodal minimization problem defined as follows:
  
  .. math::
  
      f_{\text{WayburnSeader02}}(x) = \left[ 1.613 - 4(x_1 - 0.3125)^2
                                      - 4(x_2 - 1.625)^2 \right]^2
                                      + (x_2 - 1)^2
  
  
  with :math:`x_i \in [-500, 500]` for :math:`i = 1, 2`.
  
  *Global optimum*: :math:`f(x) = 0` for :math:`x = [0.2, 1]`
  
  .. [1] Jamil, M. & Yang, X.-S. A Literature Survey of Benchmark Functions
  For Global Optimization Problems Int. Journal of Mathematical Modelling
  and Numerical Optimisation, 2013, 4, 150-194.
code: def __init__(self, dimensions=2):
      Benchmark.__init__(self, dimensions)
  
      self._bounds = list(zip([-500.0] * self.N, [500.0] * self.N))
      self.custom_bounds = ([-1, 2], [-1, 2])
  
      self.global_optimum = [[0.2, 1.0]]
      self.fglob = 0.0
  
imports: from numpy import atleast_2d, arange, sum, cos, exp, pi
  from .go_benchmark import Benchmark
label_desc: Use image node_id 1 to create a new WayburnSeader02 object from inherited base classes: Benchmark with example: obj = WayburnSeader02(dimensions)